Amazon Web Services (AWS) has upped the ante in its ongoing war of words with Oracle by taking a series of pot-shots at its rival while showcasing a growing database portfolio at Re:Invent 2017.

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The cloud services giant used the second-day keynote of its Re:Invent partner and customer conference in Las Vegas to share details of its expanding database software portfolio.

As such, the firm announced new features for its incumbent technologies, Aurora and DynamoDB, including multi-region support so users can scale out their database reads and writes across multiple datacentres, and debuted its graph database technology, Amazon Neptune.

While introducing the products, AWS CEO Andy Jassy said the expansion of its database portfolio was being driven by a customer revolt against “abusive relationships” enterprises sometimes find themselves in when working with commercial-grade database providers, before singling out Oracle as an example.

“These are companies that are very expensive, have lock-in and are proprietary, [and] really are abusive to their customers. They don’t care very much about their [customers],” he said.

“Earlier this year, Oracle – overnight – doubled the price of their software to run on AWS and Microsoft. Who does that to their customers? Someone who doesn’t care about their customers [and] somebody who views customers as a means to their financial ends.”

Echoing comments he’d made the previous day during the Partner Summit keynote at Re:Invent, Jassy claimed enterprises were increasingly looking to move away from proprietary, legacy database providers for performance and cost reasons.

“[That’s] why customers are trying to move as fast as they can to the open database engines. These are engines like MySQL, PostGres and MariaDB,” he said. “To get the same type of performance as you get on those commercial-grade databases, it is possible, but it’s hard and takes work and it’s not easy to do. So customers asked us to try to thread that needle for them.”

In a statement to Computer Weekly, an Oracle spokesperson said it would be unable to comment on the exact nature of what was said in the keynote, before going on to claim the contents of AWS’s cloud service level agreement (SLA) leave a lot to be desired.

“We would point to the AWS SLA caveats. These exclude unplanned downtime due to, among others, maintenance, software bugs, configuration changes, unplanned and planned, due to security patches,” the spokesperson said.

“Oracle’s SLA will guarantee customers 99.995% availability, bringing planned and unplanned downtime to an average of less than 2.4 minutes per month, or 30 minutes per year.”

Reinvention and new innovations

The database announcements were among 22 new products and services showcased during the keynote, with Jassy confirming this year’s Re:Invent should result in 70 additions being made to the firm’s growing portfolio of offerings.

Such is the pace of product innovation at AWS, by the close of 2017 Jassy said the company would have rolled out more than 1,300 “significant” new services and products, with users of its technology able to take advantage of an average of 3.5 new services each day.

Some of the announcements consisted of add-ons to existing products, including S3 Select and Glacier Select. These services are designed to speed up the time it takes users to extract specific pieces of data from these cloud storage repositories, and – in turn – improve the performance of the applications that depend on them.

“To enable most enterprises to use machine learning in an expansive way, we have to make it accessible for everyday developers and scientists”

Andy Jassy, AWS

The keynote also saw AWS flesh out its play in the container space, with the announcement of Amazon Elastic Container Service for Kubernetes and AWS Fargate, which Jassy said should help alleviate some of the heavy lifting users have to do when trying to make containerisation technologies run on AWS.

“For customers that want to run Kubernetes on top of AWS, there is work to do. You have to deploy a Kubernetes master, and if you want high availability you have to do that across multiple availability zones and you have to configure them to talk to each other and load balance, and it’s just work. So they [the customers] asked if there is something we could do to make it a much easier ride,” he said.

Democratisation of machine learning

At Re:Invent 2016, the company outlined its commitment to lowering the technology and skills barriers to entry for enterprises wanting to incorporate machine learning and artificial intelligence capabilities into their customer-facing applications and services.

During this year’s keynote, Jassy acknowledged there was still a lot of work to be done on this front, as the technology remains out of reach for many, but new additions to the company’s machine learning portfolio, such as Amazon Sage Maker, should help.

The aforementioned technology is billed as a managed service for developers and data scientists to use to help build, train and deploy their own machine learning models.

Along with the roll-out of AWS Deeplens, a wireless video camera that aims to provide developers with hands-on experience of using machine learning, they represent a renewed push by Amazon to help enterprises side-step the skills shortages that risk keeping machine learning off-limits to them.

“There just aren’t that many expert machine learning practitioners in the world. We’re training more at university, but there just aren’t that many,” he said.

“Most of them end up living at the big technology companies, [but] if you want to enable most enterprises and companies to be able to use machine learning in an expansive way, we have to solve the problem of making it accessible for everyday developers and scientists.”